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A deep neural network framework for real‐time on‐site estimation of acceleration response spectra of seismic ground motions

Computer-aided civil and infrastructure engineering, 2023-01, Vol.38 (1), p.87-103

2023

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An efficient algorithm to simulate site‐based ground motions that match a target spectrum

Earthquake engineering & structural dynamics, 2021-10, Vol.50 (13), p.3532-3549

2021

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Reliability Analysis of Steel SMRF and SCBF Structures Considering the Vertical Component of Near-Fault Ground Motions

Journal of structural engineering (New York, N.Y.), 2019-07, Vol.145 (7)

2019

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Interpretability and spatial efficacy of a deep-learning-based on-site early warning framework using explainable artificial intelligence and geographically weighted random forests

Di xue qian yuan., 2024-09, Vol.15 (5), p.101839, Article 101839

2024

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A generalized ground-motion model for consistent mainshock–aftershock intensity measures using successive recurrent neural networks

Bulletin of earthquake engineering, 2022-09, Vol.20 (12), p.6467-6486

2022

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Domain-informed variational neural networks and support vector machines based leakage detection framework to augment self-healing in water distribution networks

Water research (Oxford), 2024-02, Vol.249, p.120983-120983, Article 120983

2024

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Sensitivity of the response of Box-Girder Seat-type bridges to the duration of ground motions arising from crustal and subduction earthquakes

Engineering structures, 2020-09, Vol.219, p.110845, Article 110845

2020

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Generalized ground motion prediction model using hybrid recurrent neural network

Earthquake engineering & structural dynamics, 2021-05, Vol.50 (6), p.1539-1561

2021

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Fragility and vulnerability analysis of deteriorating ordinary bridges using simulated ground‐motion sequences

Earthquake engineering & structural dynamics, 2022-10, Vol.51 (13), p.3215-3240

2022

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Data-driven analysis of crustal and subduction seismic environments using interpretation of deep learning-based generalized ground motion models

Expert systems with applications, 2024-03, Vol.238, p.121731, Article 121731

2024

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Evaluation of simulated ground motions using probabilistic seismic demand analysis: CyberShake (ver. 15.12) simulations for Ordinary Standard Bridges

Soil dynamics and earthquake engineering (1984), 2021-02, Vol.141, p.106533, Article 106533

2021

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Flow forecasting for leakage burst prediction in water distribution systems using long short-term memory neural networks and Kalman filtering

Sustainable cities and society, 2023-12, Vol.99, p.104934, Article 104934

2023

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A recurrent-neural-network-based generalized ground-motion model for the Chilean subduction seismic environment

Structural safety, 2023-01, Vol.100, p.102282, Article 102282

2023

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Strength resistance factors for seismic design of exposed based plate connections in special steel moment resisting frames

Earthquake spectra, 2020-05, Vol.36 (2), p.537-553

2020

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Methodology for Validation of Simulated Ground Motions for Seismic Response Assessment: Application to CyberShake Source-Based Ground Motions

Bulletin of the Seismological Society of America, 2021-02, Vol.111 (1), p.226-241

2021

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Sensitivity Analysis of the Seismic Response of Steel Moment Frames Under Different Earthquake Scenarios

Journal of physics. Conference series, 2024-06, Vol.2647 (25), p.252006

2024

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Assessment of ground motion amplitude scaling using interpretable Gaussian process regression: Application to steel moment frames

Earthquake engineering & structural dynamics, 2023-07, Vol.52 (8), p.2339-2359

2023

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An efficient algorithm to simulate hazard-targeted site-based synthetic ground motions

Earthquake spectra, 2021-05, Vol.37 (2), p.876-902

2021

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A Bayesian network‐based probabilistic framework for updating aftershock risk of bridges

Earthquake engineering & structural dynamics, 2022-08, Vol.51 (10), p.2496-2519

2022

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Utilization of Site-Based Simulated Ground Motions for Hazard-Targeted Seismic Demand Estimation: Application for Ordinary Bridges in Southern California

Journal of bridge engineering, 2020-11, Vol.25 (11)

2020

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Statistical Frameworks for Improved Seismic Demand Analysis of Ordinary Standard Bridge Structures

Fayaz, Jawad

2021

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Deep learning-based modeling of the cyclic behavior of replaceable fuse buckling-restrained braces (BRBs)

Structures (Oxford), 2024-05, Vol.63, p.106484, Article 106484

2024

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Structural behavior of concrete beams and columns reinforced with Waste Plastic incorporated GFRP (WPGFRP) rebars

Journal of Building Engineering, 2019-05, Vol.23, p.172-184

2019

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Reliability Analysis of Steel SMRF and SCBF Structures Considering the Vertical Component of Near-fault Ground Motions

Fayaz, Jawad

2018

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Performance of Ternary Binder Blend Containing Cement, Waste Gypsum Wall Boards and Blast Furnace Slag in CLSM

Procedia engineering, 2016, Vol.145, p.104-111

2016

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A deep neural network framework for real‐time on‐site estimation of acceleration response spectra of seismic ground motions

An efficient algorithm to simulate site‐based ground motions that match a target spectrum

Reliability Analysis of Steel SMRF and SCBF Structures Considering the Vertical Component of Near-Fault Ground Motions

Interpretability and spatial efficacy of a deep-learning-based on-site early warning framework using explainable artificial intelligence and geographically weighted random forests

A generalized ground-motion model for consistent mainshock–aftershock intensity measures using successive recurrent neural networks

Domain-informed variational neural networks and support vector machines based leakage detection framework to augment self-healing in water distribution networks

Sensitivity of the response of Box-Girder Seat-type bridges to the duration of ground motions arising from crustal and subduction earthquakes

Generalized ground motion prediction model using hybrid recurrent neural network

Fragility and vulnerability analysis of deteriorating ordinary bridges using simulated ground‐motion sequences

Data-driven analysis of crustal and subduction seismic environments using interpretation of deep learning-based generalized ground motion models

Evaluation of simulated ground motions using probabilistic seismic demand analysis: CyberShake (ver. 15.12) simulations for Ordinary Standard Bridges

Flow forecasting for leakage burst prediction in water distribution systems using long short-term memory neural networks and Kalman filtering

A recurrent-neural-network-based generalized ground-motion model for the Chilean subduction seismic environment

Strength resistance factors for seismic design of exposed based plate connections in special steel moment resisting frames

Methodology for Validation of Simulated Ground Motions for Seismic Response Assessment: Application to CyberShake Source-Based Ground Motions

Sensitivity Analysis of the Seismic Response of Steel Moment Frames Under Different Earthquake Scenarios

Assessment of ground motion amplitude scaling using interpretable Gaussian process regression: Application to steel moment frames

An efficient algorithm to simulate hazard-targeted site-based synthetic ground motions

A Bayesian network‐based probabilistic framework for updating aftershock risk of bridges

Utilization of Site-Based Simulated Ground Motions for Hazard-Targeted Seismic Demand Estimation: Application for Ordinary Bridges in Southern California

Statistical Frameworks for Improved Seismic Demand Analysis of Ordinary Standard Bridge Structures

Deep learning-based modeling of the cyclic behavior of replaceable fuse buckling-restrained braces (BRBs)

Structural behavior of concrete beams and columns reinforced with Waste Plastic incorporated GFRP (WPGFRP) rebars

Reliability Analysis of Steel SMRF and SCBF Structures Considering the Vertical Component of Near-fault Ground Motions

Performance of Ternary Binder Blend Containing Cement, Waste Gypsum Wall Boards and Blast Furnace Slag in CLSM

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